GEEs with spline-based covariance functions
Modeling spatial covariance functions
... are based on the spectral representation of covariance functions, Barry and Ver Hoef (1996) proposed a nonparametric piecewise linear model for the variogram using the convolution representation of ...
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An Optimization Method Based On B-spline Shape Functions & the Knot Insertion Algorithm
... 4 Application for airfoil design The purpose of this application is to find optimum shapes to minimize the drag of transonic airfoils while keeping the lift coefficient constant and keeping the maximum thickness of the ...
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3. New iterative methods based on spline functions for solving nonlinear equations
... This paper is organized as follows. Section 2 provides some preliminaries which are needed. Section 3 is devoted to suggest two iterative methods by using a new quadrature rule based on spline ...
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Spline Representations of Functions on a Sphere for Geopotential Modeling
... Although a high-resolution global gravity model is based on surface data over the entire Earth, it must be more than a representation of a surface function. The gravitational potential is a scalar function in ...
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Testing for separability of spatial-temporal covariance functions
... for an i.i.d. multivariate proess, this likelihood-based method an be used with spatial-temporal proesses that have enough repliates over time and also with multivariate repeated measures. Haas (1998) introdued a ...
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Numerical Solution of Obstacle Problems by B Spline Functions
... Keywords: Least Square Method, Uniform B-Splines, Boundary Value Problems, Obstacle Problems 1. Introduction Variational inequality theory has become an effective and powerful tool for studying obstacle and unilateral ...
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Estimating the Wage Curve with Spatial Effects and Spline Functions
... 3 where parameter λ is the coefficient on the spatially correlated errors indicating the extent of spatial correlation between the residuals. The disturbance term v is independent and identically distributed. The ...
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GEEs: SAS Syntax and Examples
... Gains) GEEs are sometimes used to analyze longitudinal data with normal ...responses. GEEs require the specification of a marginal model, so general forms of random effects can not be handled with this ...
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Cubic spline population density functions and subcentre delimitation. The case of Barcelona
... Cubic spline functions seem more appropriate to depict the polycentricity pattern of modern urban ...cubic spline function, a delimitation strategy based on derivatives is more appropriate ...
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Generalized B-spline functions method for solving optimal control problems
... [23] Chebyshev technique is used for the expansion of the state and control variables. A Fourier-based state parametrization approach for solving linear quadratic optimal control problems was developed in [24]. ...
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Solutions of Seventh Order Boundary Value Problems Using Ninth Degree Spline Functions and Comparison with Eighth Degree Spline Solutions
... cubic spline interpolation to model the solution curve and applied the differential equation as well as the boundary conditions to solve for the unknown ...methods based on spline functions ...
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Deep Neural Networks to Learn Basis Functions with a Temporal Covariance Loss
... Similar approach with our proposed model, [Huang et al., 2015] proposed a scalable GP model for regression by applying a DNN as the feature-mapping function. The DNN is pre-trained as a stacked denoising auto-encoder in ...
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On the impact of covariance functions in multi-objective Bayesian optimization for engineering design
... acquisition functions for single-objective BO are expected improvement (EI) [9], knowledge gradient [10], and predictive entropy search ...acquisition functions for multi-objective BO which include expected ...
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Random regression models for estimation of covariance functions of growth in Iranian Kurdi sheep
... Based on the estimated values of various parameters in the present study, it could be concluded that most of the phenotypic variation of body weight in Kurdi sheep from birth to 300 day of age are due to direct ...
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Adaptive wavelet methods using semiorthogonal spline wavelets: Sparse evaluation of nonlinear functions
... are based upon biorthogonal wavelets with compactly supported primal and dual ...nal spline wavelets offer some quantitative advantages, namely small supports and good conditioning of the ...dual ...
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DEVELOPMENT OF ASSORTED SOLID OBJECT BASED ON B SPLINE
... 4. SOFTWARE DEVELOPMENT To represent heterogeneous objects, a software is developed using MATLAB and C-language. C programming is used for calculation of B-spline basis functions, which are computationally ...
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Data Visualization using Spline Functions
... shape of the curve. The data dependent constraints have been developed on one family of the parameters to introduce independent curve schemes to visualize positive, monotone and convex data. However, the other family of ...
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Cubic X-Spline Interpolatory Functions
... The X-Spline was considered to generalize the conventional spline. Here the second derivative is allowed to possess discontinuities at the knots. The magnitudes of these discontinuities are related to those ...
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Using Spline Functions to Smooth Discrete Data
... To answer this question we have used the set of data {B}, Eq. (54), with a 10% random error. The data are shown as diamonds in Fig. 2. As in the previous case the quality of the smoothing was evaluated according to Eq. ...
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Mathematical Genesis of the Spatio-Temporal Covariance Functions
... auto covariance associated to a space-time random field (Anuar et ...spatio-temporal covariance models associated to stationary or non-stationary random ...spatio-temporal covariance functions ...
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